Smart Pricing AI - Final Implementation

Overview

This is the complete Smart Pricing AI system that provides intelligent pricing optimization using machine learning. The system includes a Flask backend with a trained ML model and a responsive web frontend.

Files Included

• app.py - Main Flask application with ML model integration
• index.html - Complete frontend interface (place in static/ folder)
• smart_pricing_model.pkl - Trained machine learning model
• retail_price.csv - Training dataset
• README.md - This setup guide-
• Smart_Pricing_AI.ipynb -– Jupyter notebook used to train the model

Setup Instructions

1. Install Dependencies

pip install flask flask-cors scikit-learn pandas numpy

2. File Structure

Create the following directory structure:

smart_pricing_ai/
|├── Smart_Pricing_AI.ipynb
├── app.py
├── static/
│   └── index.html
├── smart_pricing_model.pkl
└── retail_price.csv

3. Run the Application

python app.py

The application will start on http://127.0.0.1:5000

Features

• ✅ Real-time pricing optimization
• ✅ Multiple pricing strategies (Conservative, Standard, Aggressive)
• ✅ Competitor analysis integration
• ✅ Market positioning insights
• ✅ Responsive web interface
• ✅ Sample data loading for testing

API Endpoints

• GET / - Main web interface
• POST /api/optimize - Get pricing recommendations
• GET /api/sample - Load sample data
• GET /api/health - Check system health

Model Performance

• R² Score: 0.992
• RMSE: 6.71
• Trained on 676 retail pricing records
• Supports 9 product categories

Usage

1. Open the web interface
2. Select product category
3. Fill in product details and competitor prices
4. Click "Get Pricing Recommendations"
5. Review AI-generated pricing strategies

Troubleshooting

• Ensure all dependencies are installed
• Check that the model file is in the same directory as app.py
• Verify Flask is running on the correct port
• Use "Load Sample Data" to test functionality

Support

The system is fully functional and tested. All JavaScript issues have been resolved and the ML model is properly trained and integrated.